speaker segmentation

Introduction

The Pyannote Speaker Segmentation model is a part of the Pyannote.audio library, designed for automatic speech segmentation tasks. It enables the identification of different speakers within an audio file based on their speaking turns. This model is particularly useful in various applications, such as automatic transcription services and audio analysis.

Architecture

The model leverages the Pyannote.audio framework. It is an end-to-end neural network architecture that processes audio data to detect and segment speaker turns. The model is trained on datasets such as AMI, DIHARD, and VoxConverse, which are commonly used in speaker diarization research.

Training

The Pyannote Speaker Segmentation model is trained using diverse datasets to ensure robustness and accuracy. The training process involves learning to differentiate between speakers based on audio features, with a focus on handling overlapping speech and speaker changes.

Guide: Running Locally

To run the Pyannote Speaker Segmentation model locally, follow these steps:

1. Installation:

   • Visit the installation instructions for setting up Pyannote.audio.

2. Setup:

   • Accept the user conditions at hf.co/pyannote/segmentation.
   • Create an access token at hf.co/settings/tokens.

3. Code Execution:

   • Instantiate the pretrained speaker segmentation pipeline:

     from pyannote.audio import Pipeline
     pipeline = Pipeline.from_pretrained("pyannote/speaker-segmentation")
     output = pipeline("audio.wav")
     
     for turn, _, speaker in output.itertracks(yield_label=True):
         # speaker speaks between turn.start and turn.end
         ...
     

4. Notes:

   • This pipeline does not cover speaker diarization. For diarization tasks, refer to pyannote/speaker-diarization.

Cloud GPU Suggestion

For improved performance, consider using cloud GPU services such as AWS, Google Cloud Platform, or Azure to run the model, especially for processing large audio files or real-time applications.

License

The Pyannote Speaker Segmentation model is available under the MIT License, allowing for extensive use and modification in both academic and commercial settings.